class_docstr: Blur an image using the median filter.
  
  Args:
      kernel_size: the blurring kernel size.
  
  Returns:
      the blurred input tensor.
  
  Shape:
      - Input: :math:`(B, C, H, W)`
      - Output: :math:`(B, C, H, W)`
  
  Example:
      >>> input = torch.rand(2, 4, 5, 7)
      >>> blur = MedianBlur((3, 3))
      >>> output = blur(input)
      >>> output.shape
      torch.Size([2, 4, 5, 7])
code: def __init__(self, kernel_size: tuple[int, int] | int) -> None:
      super().__init__()
      self.kernel_size = kernel_size
  
file_path: kornia/kornia/filters/median.py
imports: from __future__ import annotations
  import torch.nn.functional
  from kornia.core import Module, Tensor
  from kornia.core.check import KORNIA_CHECK_IS_TENSOR, KORNIA_CHECK_SHAPE
  from .kernels import _unpack_2d_ks, get_binary_kernel2d
label_desc: Use image node_id 1 to create a new MedianBlur object from inherited base classes: Module with example: obj = MedianBlur(kernel_size)